STATISTICAL PROBABILITY OF CONTAGION BEFORE THE EFFECTIVENESS OF VACCINES AGAINST COVID-19: REFLECTION

• Autores: Argota Pérez, George, Álvarez-Becerra, Rina María, Argota-Pérez, Yadira, Iannacone, José
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Ricardo Palma
• Repositorio: Revistas - Universidad Ricardo Palma
• Lenguaje: español
• OAI Identifier: oai:oai.revistas.urp.edu.pe:article/4807
• Enlace del recurso: http://revistas.urp.edu.pe/index.php/Biotempo/article/view/4807
• Nivel de acceso: acceso abierto
• Materia: COVID-19; efficacy; SARS-CoV-2; statistical probability; vaccine; eficacia; probabilidad estadística; vacuna

The aim of the study was to refl ect on the statistical probability of contagion given the effi cacy of vaccines against COVID-19. The study was carried out in January and February 2022 where 250 articles were analyzed from the ScienceDirect database and which referred to the eff ectiveness of vaccines against COVID-19. Th e articles corresponded to the type: review, research, case report, discussion, and brief communications. Th e search keys referred to 1st) type of vaccines, 2nd) representative size of the sample, 3rd) confi dence intervals of uncertainty, 4th) type of parametric and nonparametric test, 5th) p-value threshold of statistical signifi cance, and 6th) conclusion’s act argument. Two populations of 100 people were considered under the administration of vaccine A: NT162b2 mRNA/Pfi zer-BioNTech and vaccine B: COVID-19 absorbed: inactivated/CoronaVac in the other population. A simultaneous vaccination program was assumed, recognizing the probability of selecting a person with one or another vaccine through the expression: P(A ∪ B) = P(A) + P(B) where the probability was 0.73%, which indicates, lower the risk of the severe and/or critical condition of COVID-19, but it must be interpreted that the mathematical model is not distant from the biological model. It is concluded that it is necessary to continue the reflection on the significance of probability in the report of vaccine efficacy since decisions must be based on explanations from statistical models of vaccination and data science for protection against COVID-19.